Security Returns Research Articles

Bubbles and crashes in a Black–Scholes model with delay

This paper studies the asymptotic behaviour of an affine stochastic functional differential equation modelling the evolution of the cumulative return of a risky security. In the model, the traders of the security determine their investment strategy by comparing short- and long-run moving averages of the security’s returns. We show that the cumulative returns either obey the law of the iterated logarithm, but have dependent increments, or exhibit asymptotic behaviour that can be interpreted as a runaway bubble or crash.

Research on Audience Rating Statistics of Two-way Digital TV Based on OpenSSL

The drawback of the present various forms of digital program audience statistical method is that only the traditional phone questionnaire survey, the diary method or the artificial equipment is applied to counting the situation of watching program. By means of combining the timely recognized operation property of various digital terminals and automatic return viewing program feature, a new scheme is proposed to count audience situation for program in two-way digital television network. The main technologies and functions of the scheme are described by introducing audience information gathering mechanisms, security return protocol stack based on openSSL, fusion and automatic transmission and its appropriate statistical methods. Meanwhile, the development of the audience rating statistical system is provided, which is used by some program providers according to this scheme. The experiment and users’ feedback show that this scheme in the lower hardware configuration digital terminals can promptly and accurately count the subscribers watching program and effectively protect audience view information.

Model Capital Asset Pricing Model (CAPM) dan Arbitrage Pricing Theory (APT) Dalam Memprediksi Imbal Hasil Saham (Return Saham) Di Bursa Efek Indonesia (BEI)

The objective of this research is to analysis the influence of a market risk, inflation, and rate of exchange toward return of securities with CAPM and APT models. The research will use correlation and multiple regression analysis model with several hypothesis test:determination coefficient (R2 ), Anova (Fisher test), and t- test (student test). Data processed by SPSS program (Statistic and Product Services Solution) version 17.0. The research has used dependent variable is return of securities and independent variable are mrket risk, inflation, and rate of exchange . The determinant coefficient analysis CAPM models show that market risk amount 0.559 (55.9%) and the rest 0.441(44.1%) should be caused by other variables. While in APT models, inflation, and rate of exchange influences toward return of securities amount 0.184 (18.4%) and the rest 0.816 (81.6%) should be caused by other variables. The hypothesis test with used F test shown that of independent variable market risk, inflation, and rate of exchange as joint influence significantly toward return of securities variable significance rate 0.000. The hypothesis test as single with used t test shown that market risk, inflation, and rate of exchange influence significantly toward return of securities.

Portfolio selection using mean-risk model and mean-risk diversification model

With mean-risk and mean-risk diversification models, return distributions are characterised and compared using two statistics: the expected value and the value of a risk measure. This paper uses mean-risk model and risk curve obtained from the same model for portfolio selection problem. Security returns are assumed to be normally distributed. Further, the same mean-risk model is modified by using entropy to diversify the risk; this model can be called as mean-risk diversification model. In both the models, normal distribution is used to calculate the probability of likely losses of portfolio. The idea of mean-risk model is to regard expected return of a portfolio as the investment return and risk curve thus formed as investment risk, and the idea of mean-risk diversification model is to ensure that the portfolio thus formed is well diversified. The objective is to maximise the investor’s return at a preset confidence level and minimise the risk. Two numerical examples are presented for the sake of illustr...

The Effect of Taxes on Conventional Preferred Stock: Evidence from the 2003 JGTRRA Dividend Tax Reduction

ABSTRACT This study examines the extent to which investor-level taxes affect the pricing and pre-tax returns of securities. Specifically, we investigate whether the pre-tax yield on outstanding conventional preferred stock (CPS) decreased after the 2003 Jobs and Growth Tax Relief Reconciliation Act (JGTRRA) reduced the individual's tax rate on dividends. Our research design for detecting tax effects is strong for two reasons: (1) JGTRRA provides a quasi-experimental setting that permits a pre/post design, and (2) we use trust preferred stock (TPS) issued by the same firm as the tax-disfavored benchmark asset, which permits a matched-pair design that controls for risk. Additional tests including CPS issues without TPS counterparts confirm the effect of JGTRRA on CPS issues. The results indicate that investors reacted to the new tax-favored status of CPS by bidding up its price, which lowered its yield. Data Availability: All data are available from public sources identified in the paper.

An Examination of Herd Behavior: An Empirical Evidence from Indian Equity Market

The paper aims to study the effect of herding in Indian equity market. The authors have tested the presence of herding using data from National Stock Exchange (NSE) and methodology as described in Christie and Huang (1995) and Chang, Cheng and Khorana (2000). Security return dispersion as a function of aggregate market return has been taken as a proxy for herd behavior. To test the presence of herding linear regression model and linear regression using quadratic functional form has been applied. Previous studies have reported the presence of herding in emerging Asian economies. However no evidence has been found in developed economies. The result of the study endorses the fact that Indian markets are efficient as no severe herding has been reported. However when presence of herding was tested for periods of market stress, it prevailed in bull phase.

Mean–variance models for portfolio selection subject to experts’ estimations

Since the security market is complex, sometimes the future security returns are available mainly based on experts judgements. This paper discusses a portfolio selection problem in which security returns are given subject to experts’ estimations. The use of uncertain measure is justified, and two new mean–variance and mean–semivariance models are proposed. In addition, a hybrid intelligent algorithm for solving the optimization models is given. To illustrate the application of the new models, the method to obtain the uncertainty distributions of the security returns based on experts’ evaluations is given, and two selection examples are provided.

Catastrophes and Insurance Stocks – A Benchmarking Approach for Measuring Efficiency

AbstractThis study uses the numeraire portfolio to benchmark insurance stock returns as a natural measure for detecting abnormal insurance stock returns from catastrophic events. The assumptions underlying the efficient markets hypothesis using a numeraire denominated returns approach hold for catastrophic insurance events whereas other more traditional methods such as the market model and Fama-French three factor model often fail, typically due to the accumulation of estimation errors. We construct a portfolio of Australian insurance firms and observe the market reaction to major insured catastrophic events. Using the numeraire denominated returns approach we observe no particular trend in the cumulative abnormal returns of insurance securities following a catastrophic event. Using both the traditional market model and the Fama-French three factor model however, we observe significantly positive cumulative abnormal returns following an insured catastrophic event. The errors inherent in the market model and three factor model for event studies are shown to be eliminated using the numeraire denominated returns approach.

Constructing the best trading strategy: a new general framework

A new general framework for constructing the best trading strategy for a given historical indicator is introduced in this paper. We construct the unique trading strategy with the highest expected return. This optimal strategy may be implemented directly, or its expected return may be used as a benchmark to evaluate how far away other proposed strategies for the given indicators are from the optimal. Separately, we also construct the unique trading strategy with the highest information ratio. In the normal case, when the traded security return is near zero, and for reasonable correlations, the performance differences are economically insignificant. However, when the correlation approaches 1, the trading strategy with the highest expected return approaches its maximum information ratio of 1.32, while the trading strategy with the highest information ratio goes to infinity.

A Krylov Subspace Approach to Large Portfolio Optimization

With a large number of securities (N) and fewer observations (T), deriving the global minimum variance portfolio requires the inversion of the singular sample covariance matrix of security returns. We introduce the Break-Down Free Generalized Minimum RESidual (BFGMRES), a Krylov subspaces method, as a fully automated approach for deriving the minimum variance portfolio. BFGMRES is a numerical algorithm that provides solutions to singular linear systems without requiring ex-ante assumptions on the covariance structure. Moreover, it is robust to illiquidity and potentially faulty data. US and international stock data are used to demonstrate the relative robustness of BFGMRES to illiquidity when compared to the “shrinkage to market” methodology developed by Ledoit and Wolf (2003). The two methods have similar performance as assessed by the Sharpe ratios and standard deviations for filtered data. In a simulation study, we show that BFGMRES is more robust than shrinkage to market in the presence of data irregularities. Indeed, when there is an illiquid stock shrinkage to market allocates almost 100% of the portfolio weights to this stock, whereas BFGMRES does not. In further simulations, we also show that when there is no illiquidity, BFGMRES exhibits superior performance than shrinkage to market when the number of stocks is high and the sample covariance matrix is highly singular.

Another Specification of Ohlson's ‘Other Information’ Term for the Earnings/Returns Association: Theory and Some Evidence

Abstract: Following Ohlson (2001) we characterize a variable that represents the ‘other information’ term in the Ohlson (1995 and 2001) framework using the security return specification. We interpret this variable as capturing the market's expectation that earnings change will persist into the future. This expectation can be measured using data that is readily available to capital markets researchers: future forecasts of earnings and realized accounting earnings. We show in a returns context that expectations for accelerating (decelerating) earnings growth are rewarded (discounted) by the market. While omitting other information may not be important in a reasonably long window such as a year, it becomes crucial in a shorter window. Even in the annual window, the inclusion of the earnings change persistence variable significantly improves explanatory power of the Ohlson model for returns. Finally, we offer evidence that the association of returns with earnings levels and changes observed in annual windows is robust to the quarterly time frame and we establish that the proper specification for quarterly earnings change is consecutive, not seasonal.

A new risk criterion in fuzzy environment and its application

Since the observed values of security returns in real-world problems are sometimes imprecise or vague, an increasing effort in research is devoted to study the properties of risk measures in fuzzy portfolio optimization problems. In this paper, a new risk measure is suggested to gauge the risk resulted from fuzzy uncertainty. For this purpose, the absolute deviation and absolute semi-deviation are first defined for fuzzy variable by nonlinear fuzzy integrals. To compute effectively the absolute semi-deviations of single fuzzy variable as well as its functions, this paper discusses the methods of computing the absolute semi-deviation by classical Lebesgue–Stieltjes (L–S) integral. After that, several useful absolute deviation and absolute semi-deviation formulas are established for common triangular, trapezoidal and normal fuzzy variables. Applying the absolute semi-deviation as a new risk measure in portfolio optimization, three classes of fuzzy portfolio optimization models are developed by combining the absolute semi-deviation with expected value operator and credibility measure. Based on the analytical representation of absolute semi-deviations, the established fuzzy portfolio selection models can be turned into their equivalent piecewise linear or fractional programming problems. Since the absolute semi-deviation is a piecewise fractional function and pseudo-convex on the feasible subregions of deterministic programming models, we take advantage of the structural characteristics to design a domain decomposition method to separate a deterministic programming problem into three convex subproblems, which can be solved by conventional solution methods or general-purpose software. Finally, some numerical experiments are performed to demonstrate the new modeling idea and the effectiveness of the solution method.

Composition of an efficient portfolio in the Bielecki and Pliska market model

We study the continuous time portfolio optimization model due to Bielecki and Pliska where the mean returns of individual securities or asset categories are explicitly affected by underlying economic factors. We introduce the functional Qγ featuring the expected earnings yield of portfolio minus a penalty term proportional with a coefficient γ to the variance when we keep the value of the factor levels fixed. The coefficient γ plays the role of a risk-aversion parameter. We find the optimal trading positions that can be obtained as the solution to a maximization problem for Qγ at any moment of time. The single-factor case is analyzed in more details. We present a simple asset allocation example featuring a Vasicek-type interest rate which affects a stock index and also serves as a second investment opportunity. Then we compare our results with the theory of Bielecki and Pliska where the authors employ the methods of the risk-sensitive control theory thereby using an infinite horizon objective featuring the long run expected growth rate, the asymptotic variance, and a risk-aversion parameter similar to γ.

Multi-objective Model for Uncertain Portfolio Optimization Problems

This paper discusses the portfolio optimization problems in which the security returns are assumed to be uncertain variables that are neither random nor fuzzy. Regarding the security returns as uncertain variables, this paper proposes three new multi-objective models for portfolio selection based on the uncertainty theory. Since there is no efficient method to solve the proposed models until now, the original multi-objective models will be transformed into their corresponding crisp equivalents form when the securities are chosen as some special uncertain variables, and then the classical algorithm NSGA-II is used to solve these new models. The presented numerical examples illustrate the application of the new models and show their robustness and adaptability.

The Information Content Of Concurrently Announced Quarterly Earnings And Dividends

This research hypothesizes that concurrently announced earnings and dividends have a multiplicative effect on residual security returns. To test the hypothesis, residual returns are regressed on unexpected earnings and unexpected dividend variables, as well as on dummy variables defined based on their signs. Using a sample of same-day announcements of earnings and dividends over an 80-month period, it is shown that only the dummy variables, which reflect multiplicative effects, are useful in explaining security returns.

Earnings Versus Cash Flow: The Information Provided About Changes In Company Liquidity

Recent research has examined the use of earnings versus cash flow in such areas as explaining abnormal security returns, predicting corporate bankruptcy, and predicting future company cash flow. This study extends prior research on the information provided by earnings and cash flow to the area of explaining changes in company liquidity. Univariate and multivariate regressions are used to examine the relationships between annual changes in the accounting flow variables and changes in liquidity.

The Effect Of Changes In The Dollar Foreign Exchange Rate On Stock Returns Of Multinational Corporations

<span>Exchange rate movements are considered to be one of the key factors affecting the operating results of multinational corporations (MNC). Several studies have examined the effect of changes in dollar exchange rates on the stock prices of MNC. The results of these studies have been inconclusive about the effects of changes in the dollar exchange rate on the stock prices of companies with significant overseas operations. This study extends previous research by testing the impact of changes in the dollar exchange rate on security returns of MNC using an event study methodology. The results suggest that changes in dollar exchange rates have little or no impact on the stock returns of MNC.</span>

Holdings Data, Security Returns, and the Selection of Superior Mutual Funds

Holdings Data, Security Returns, and the Selection of Superior Mutual Funds

Fuzzy-Portfolio-Selection Models With Value-at-Risk

Based on fuzzy value-at-risk (VaR), this paper proposes a new portfolio-selection model (PSM) called the VaR-based fuzzy PSM (VaR-FPSM). Compared with the existing FPSMs, the VaR can directly reflect the greatest loss of a selected case under a given confidence level. In this study, when the security returns are taken as trapezoidal, triangular, and Gaussian fuzzy numbers, several crisp equivalent models of the VaR-FPSM are derived, which can be handled by any linear programming solvers. In general situations, an improved particle swarm optimization algorithm on the basis of fuzzy simulation is designed to search for the approximate optimal solutions. To illustrate the proposed model and the behavior of the improved particle swarm optimization algorithm, two numerical examples are provided, and the results are discussed. Furthermore, the proposed algorithm is compared with some existing approaches to fuzzy portfolio selection, such as the genetic algorithm and simulated annealing.

A modified Corrado test for assessing abnormal security returns

Event studies typically use the methodology developed by Fama et al. [1969. The adjustment of stock prices to new information. International Economic Review 10, no. 1: 1–21] to segregate a stock's return into expected and unexpected components. Moreover, conventional practice assumes that abnormal returns evolve in terms of a normal distribution. There is, however, an increasing tendency for event studies to employ non-parametric testing procedures due to the mounting empirical evidence which shows that stock returns are incompatible with the normal distribution. This paper focuses on the widely used non-parametric ranking procedure developed by Corrado [1989. A nonparametric test for abnormal security price performance in event studies. Journal of Financial Economics 23, no. 2: 385–95] for assessing the significance of abnormal security returns. In particular, we develop a consistent estimator for the variance of the sum of ranks of the abnormal returns, and show how this leads to a more efficient test statistic (as well as to less cumbersome computational procedures) than the test originally proposed by Corrado (1989). We also use the theorem of Berry [1941. The accuracy of the Gaussian approximation to the sum of independent variates. Transactions of the American Mathematical Society 49, no. 1: 122–36] and Esseen [1945. Fourier analysis of distribution functions: A mathematical study of the Laplace–Gaussian law. Acta Mathematica 77, no. 1: 1–125] to demonstrate how the distribution of the modified Corrado test statistic developed here asymptotically converges towards the normal distribution. This shows that describing the distributional properties of the sum of the ranks in terms of the normal distribution is highly problematic for small sample sizes and small event windows. In these circumstances, we show that a second-order Edgeworth expansion provides a good approximation to the actual probability distribution of the modified Corrado test statistic. The application of the modified Corrado test developed here is illustrated using data for the purchase and sale by UK directors of shares in their own companies.